Author: KK.aWSB

Let me share a real experience that many people had over the past three years, where a group of people traded stocks with great satisfaction.

Their method was so simple it hardly seemed like a method: buy Nvidia, or those few tech giants or the storage sector with your eyes closed, and just hold on. Buy more when it goes up, add to your position when it drops, and basically don't think much.

What happened? Nvidia's market value soared to the top in the world, breaking through $50 trillion; those big tech companies took turns breaking historical records. This group of people made a fortune and summed it up with the insight: "Don't overthink it, AI is the future, just buy along."

This is what is referred to as the "simple model"—a phase where even ordinary people can easily participate, and there is a high likelihood of making money.

However, as we enter 2026, something is quietly happening: this simple model may have already ended.

It's not that AI isn't working, nor that the bull market is over. Rather, this game has switched from the "simple model" to the "difficult model." The old "buy with your eyes closed" strategy is becoming increasingly ineffective.

In today's article, I want to clarify this: What exactly is the "simple model"? Why did it end? And what should ordinary people do when the difficulty of the game increases?

No jargon, no bookish phrases, just principles and methods.

First, understand: how did the "simple model" come about?

To determine whether the simple model is still in place, we need to understand why it appeared in the first place.

Many people have a misconception that the ease of making money over the past three years was because "AI is a big trend."

This is only half right. Just having a trend isn’t enough for ordinary people to make easy money. What truly made it "simple" was another element—the dividend of information disparity.

Any truly disruptive new technology will go through a special phase in its early stages: its enormous potential is already quite clear; however, the market hasn’t yet had the time to fully reflect this potential in stock prices.

The gap between this "visible future" and "prices that haven't adjusted yet" is the dividend.

What made AI unique in its early days was:this dividend was ridiculously large and remarkably simple. The demand was so certain—everyone in the world needed to buy chips and build data centers, and there were only a few companies that could provide these services. The logic was simple enough that even an ordinary person who knows nothing about technology could understand: buy from those who sell shovels. This is why Nvidia became the standard answer for "buy with your eyes closed."

So the essence of the "simple model" is not about the market being generous but rather: a massive, obvious opportunity that hasn’t yet been fully priced in. What you earned was money from this "time difference."

But remember a hard rule: any obvious dividend will be slowly consumed as more and more people flood in. This is not a question of "if," but "when."

Three signals: the simple model is closing

So how can we judge that the dividends have been largely consumed and the game is switching difficulty? Look for three signals that are currently happening.

Signal one: the "buy with your eyes closed" standard answer is not working anymore.

This is the most straightforward and also the most counterintuitive signal.

In the past three years, buying those few tech giants (commonly referred to as the "Magnificent Seven") was synonymous with guaranteed profits. However, in the first half of 2026, something happened that shocked everyone:

these seven star giants, as a whole, actually had a negative return for the year.

Meanwhile, the remaining 493 "ordinary companies" in the S&P 500 index saw their stock prices rise over 10%—almost double that of the Magnificent Seven.

You read that right. The very leaders that had led everyone on a crazy run are now lagging behind the market and dragging it down. The standard answer that used to be "buy with your eyes closed" has failed for the first time.

What does this indicate? When an opportunity becomes easy and well known to everyone, and everyone rushes in, it ceases to be an opportunity. Because the benefits have been preemptively overdrawn, and prices have risen ahead of the future.

Signal two: the market is starting to "demand accountability."

The second signal is a change in the market's attitude.

Over the past three years, the tech giants went on a spending spree to develop AI, and the market was cheering them on—the more you announced you were investing, the higher your stock price would go. Because everyone believed: "spending money = optimistic about the future = will make big profits later."

However, in 2026, the winds changed completely.

The AI-related expenditures of these giants are expected to surge to over $700 billion in 2026, nearly an 80% increase from last year. Yet the market's reaction is no longer applause but frowning:

"The money has been spent, but what about profits? When will we see a return?"

A particularly sobering statistic shows that although most companies are still aggressively investing in AI, most AI projects are currently not profitable.

Thus, the market's mindset has shifted from "rewarding you for spending" to "demanding returns." This shift is a core sign of the end of the simple model. What people bought in the past were 'stories', now they want to see 'results.'

Signal three: extreme volatility that can change on a dime.

The third signal is that the market’s behavior has changed—it has become increasingly "nervous."

In June 2026, a typical severe fluctuation occurred: in just two days, due to collective worries about "whether AI spending has gone overboard," tech stocks plummeted, with the Nasdaq index dropping 2.2% in a single day. Since the end of May, the seven giants have lost about $2.3 trillion in market value within a month.

Such "flip-flopping" volatility is rarely seen in the simple model. It reveals a collective anxiety: everyone has made a lot of money, is at a high, and is afraid of being the last one to leave the party. Thus, at the first sign of trouble, they all rush for the exits.

When a market begins to experience frequent sharp upswings and downswings, it often indicates that the era of easy profits has passed, and smart money is becoming cautious.

But be aware: increased difficulty does not mean game over

At this point, you might think I am going to say, "The AI bubble is about to burst, run!"

Quite the opposite. This is the most crucial and also the easiest point to misunderstand.

The "end of the simple model" and the "end of AI investment" are completely different things.

To illustrate, let’s compare the past three years of AI investment to climbing a mountain:

The first three years were like a cable car. You only had to get on (buy that standard answer), and it would automatically take you up. Anyone could do it without needing any skills.

But now, the cable car has arrived at its stop, and the rest of the way requires you to climb on your own. The mountain is still there, and the peak might still be far off—but from here on out, who can go up and how high depends on your judgment, not luck.

Here are a few reasons to show that "the mountain is still there":

Although those giants have stock price fluctuations, their AI business demands are still real and at record levels—this is fundamentally different from those companies during the internet bubble that "had only a story, but no revenue." Today's AI giants are genuinely making money; it’s just that the market feels they "aren't earning enough compared to what they're spending."

Furthermore, the mainstream assessments from major Wall Street firms are quite consistent: this decline is not the "start of a crash," but a "shift from trading stories to competing for performance." The game has not ended; the rules have just tightened.

So what truly happened is not the "collapse of the AI myth" but rather "AI investment transitioning from a beginner level to an advanced level." The era of blind speculation is over; the next phase is a real test of skill.

In difficult mode, how should ordinary people play?

Now the question arises: Without the cable car, can ordinary people still participate? How should they do so?

Here are four principles for you. They don’t guarantee profit (no method can assure that), but they can help you avoid fatal mistakes in difficult mode.

First, upgrade from "buy the trend" to "look for results."

In the simple model, you only needed to judge whether "the AI trend is viable"—the answer is clearly yes. But in difficult mode, that judgment is no longer valuable because everyone knows it.

The new task is: distinguish which companies in AI are "truly profitable" and which are just "telling stories." Is a company already producing real profits, or are they merely painting a blueprint that hasn't yet materialized? This distinction was not important in the simple model; in difficult mode, it makes the difference between success and failure.

Second, be wary of what "everyone is buying."

This is the most counterintuitive, yet the most important rule.

When a stock or a trend is already on every headline, every dining table, and the lips of every relative—this is often not a buying signal, but rather a dangerous signal. Because it implies that everyone who needed to buy has already done so, the price has been pushed to the peak, and the question becomes—who will buy next?

Remember: stay vigilant when others are greedy. Easy, well-known money is usually the most dangerous money.

Third, don’t mistake "one basket" for "many baskets."

Many people think they have purchased "a bunch of different tech stocks," believing it to be diversified and safe. But the truth is: these stocks nearly move in sync. They are all based on the same logic (AI spending), bound by the same chain—when one flourishes, they all prosper, and when one suffers, they all suffer.

This is called "the illusion of diversification": you think you have bought many things, but in reality, you have put your entire fortune on the same bet. True diversification is to ensure your money does not solely rely on whether the AI story pans out.

Fourth, and this one is the simplest: only use "money you can afford to lose."

The biggest characteristic of difficult mode is that fluctuations will become severe—today it's up 5%, tomorrow it's down 8%, and that's routine.

In such an environment, what determines whether you can survive often isn’t how accurate your judgments are, but rather how stable your mindset is. The only condition for a stable mindset is: the money you’ve invested is that "even if you lost it all, it won’t affect your life or your sleep." Because those who "can't afford to lose" will definitely panic and cut losses at the most frantic moments when they shouldn't.

Finally

Returning to the initial question: is it still the "simple model" to trade stocks along the AI mainline?

My answer is: the simple model that allowed you to make money with your eyes closed has likely ended. However, the grand play that is AI is far from over.

What has changed is the difficulty; what remains unchanged is that this direction is still one of the most important waves of this era.

This is actually the fate of all investments—whenever an opportunity becomes so simple that everyone knows about it, the dividends are already on the path to being consumed. The true long-term winners are never those who got lucky and hopped onto a cable car, but rather those who, after the cable car stops, still know how to keep climbing.

The simple model rewards those who "dare to get on the ride."

The difficult model rewards those who "know how to walk."

Most people will panic and get off the ride at the moment the cable car stops, or they will complain in place.

A few will quietly tie their shoelaces and start learning how to climb the mountain on their own.

And from this point onward, these two types of people will end up in completely different places.

(Note: This article discusses principles and thinking strategies related to investing and does not constitute any specific trading suggestions. The market has risks, and each person's decisions should be made based on their personal situation.)

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